Abstract
Cloud contamination is one of the major barriers for wider applications of MODIS snow cover products. This study presents a cloud-removal approach, through multiday backward replacements based on Terra and Aqua daily MODIS snow cover products (MOD10A1 and MYD10A1), to generate a series of daily cloud-free snow cover products for advanced applications (MODMYD_MC). The products are evaluated using in situ snow depth data measured during 2000 to 2010 at 53 weather stations in the Heilongjiang Province, northeast China. The results show that the annual mean cloud covers of MOD10A1, MYD10A1, MODMYD_DC (the daily combination of MOD10A1 and MYD10A1), and MODMYD_MC are 50%, 54%, 35%, and 0%, mean snow covers are 6%, 6%, 10%, and 19%, and their mean agreements of snow cover mapping are 42%, 40%, 51%, and 91%, respectively. The snow-covered days (SCDs) derived from MODMYD_MC are also in good agreement (91%) with those obtained from in situ observations. The MODMYD_MC snow cover images are then used to investigate the detailed variation of snow cover in the XiaoXing’AnLing watershed. The snow-covered area in the watershed has an increasing trend in the recent decade, with the minimum present in the 2002 (hydrologic year) and the maximum present in 2010. The plains with lower elevation show shorter SCD but larger interannual variations than in the mountainous areas. This study indicates that MODMYD_MC can be applied to monitor the spatiotemporal variations of snow cover in northeast China and elsewhere in the world.
Highlights
Snow has a significant impact on surface energy balance, crop frost, and water cycles due to its high albedo, thermal insulation, and melting water.[1]
I1⁄41 where A represents the area of each pixel (0.25 km2), SCDi refers to the snow-covered days (SCDs) in a hydrological year for pixel i, and N is the total pixels in the study area, i.e., the XiaoXing’AnLing watershed labeled by the white polygon in Fig. 8 in this study
The daily combination of Terra and Aqua moderate resolution imaging spectral radiometer (MODIS) snow cover products is based on the snow priority algorithm developed by Xie
Summary
Snow has a significant impact on surface energy balance, crop frost, and water cycles due to its high albedo, thermal insulation, and melting water.[1]. We present a new multiday backward cloud-removal approach to produce daily cloud-free snow cover product The first step is to combine the snow cover images of MOD10A1 and MYD10A1 to generate a daily maximum snow cover image called MODMYD_DC.[10] The second step is a multiday backward replacement, i.e., the cloud-blocked pixels on the current day combination of MODMYD_DC (n) are replaced by the cloud-free pixels on the previous day combination of MODMYD_DC (n − 1), continuing the backward replacement on day (n − k) until all cloud-blocked pixels are replaced. As the CPD gets larger, the new cloud-free snow cover image has a greater uncertainty
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